Population Dynamics of Largemouth Bass and Panfish in South Dakota Ponds

Spring electrofishing samples were collected from 13 small impoundments in 1988 to determine relationships between largemouth bass Micropterus salmoides and bluegills Lepomis macrochirus in South Dakota. Largemouth bass catch per hour of electrofishing, defined as catch per unit effort (CPUE) for stock-length fish, was inversely correlated with bass proportional stock density (PSD) (i= - 0.70, P=0.01), and relative stock density of preferred-length bass (RSD-P) (r = -0.79, P=0 .001). Largemouth bass CPUE was positively correlated with bluegill PSD (r = 0.72, P=0.02). Largemouth bass PSD was inversely correlated with bluegill PSD (r=- 0.83, P=0.003); bluegill PSD exceeded 60 only when largemouth bass PSD was less than 20. Bluegill PSD was inversely correlated with largemouth bass mean relative weight (Wr) (r =- 0.72, P=0.02). Largemouth bass CPUE and RSD-P were inversely correlated with bluegill growth. In 1989, eight small South Dakota impoundments were sampled to evaluate relationships between largemouth bass and yellow perch Perca flavescens. Largemouth bass CPUE was positively correlated with yellow perch PSD 9(r = 0.81, P=0.02). Largemouth bass PSD was inversely correlated with yellow perch PSD (r= -0.82, P=0.01). Mean relative weight (Wr) of yellow perch was inversely correlated with RSD-P of largemouth bass (r = 0.71, P=0.05). Yellow perch growth was inversely correlated with largemouth bass size structure. The highest correlation was noted between mean back-calculated length of yellow perch at age 4 and largemouth bass PSD (R = -0.95, p=0.01). Seven environmental factors (i.e., aquatic vegetation coverage, specific conductance, Secchi disk transparency, surface area, maximum depth, total alkalinity, turbidity) were measured to determine the relationship between largemouth bass density and environmental variables in the ponds sampled in 1988 and 1989. Largemouth bass CPUE was positively correlated with aquatic vegetation coverage (r = 0.65, P=0.001) and Secchi disk transparency (r = 0.48, P=0.032). In addition, multiple regression analysis with these two variables produced a significant model (P=0.0016) that accounted for 51% (R2=0.51) of the variability in largemouth bass CPUE.